arXiv (All)
open access
TRIAGE: Three-level Routing and Intelligent Agent Guidance for Efficient Execution
Large Language Model (LLM) agents based on the ReAct paradigm have demonstrated remarkable capabilities in tool use and task execution. However, ReAct suffers from a fundamental efficiency problem: every query triggers a complete reasoning loop from scratch, and similar queries repeat identical step
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Harness Engineering in LLM Tool Use via Agent-Native Reusable Tool Primitives#822166
- PetriBench: Benchmarking LLM Reasoning over Dynamic State Spaces#1014930
- E2E-SWE: Benchmarking LLMs on Building Working Codebases from Scratch#1169651
- E2E-SWE: Benchmarking LLMs on Building Working Codebases from Scratch#1142936
- Projecting the Emerging Mindset of SWE Agent by Launching a Wild Code Understanding Journey#267724
Record · ID 821362
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive